Application Observability | 리소스 센터

Every level of the application stack emits logs, metrics, traces, and events. Collecting all these signals is the first step in having an observable system. See how Open Telemetry makes this possible.

Forward-looking companies are embracing reliability management. Learn how they're measuring business outcomes rather than system performance.

Delivering value to customers quickly and efficiently is critical to the success of modern businesses. Understanding the process and timeframe during which an organization generates new ideas and then designs, develops and deploys them is vital to success.

We are living in a data world. Data describes and controls almost every aspect of our life, from the president's elections to everyday grocery shopping. Data grows exponentially and so does the complexity of applications that manage that data.

Consumers and users of applications expect near 100% availability and reliability to work, transact, collaborate, etc. There’s a lot of talk about monitoring the performance of the application itself, but what about the underlying systems and components supporting the app, and in particular the infrastructure it sits on?

Technology environments are rapidly evolving as organizations look to remain competitive, accelerate innovation and make themselves more agile. But in the process, many of the observers, i.e., stakeholders who track infrastructure and application metrics, are falling behind, unable to monitor and manage modern, cloud-native apps and multi-cloud environments due to the complexity that comes with them.

SDO helps you track siloed data across the DevOps toolchain. It normalizes and correlates data, provides you with DORA’s 4 key metrics and gives you deep insights into the velocity and quality of delivery across services and teams.

Amazon Elastic Kubernetes Service, or EKS, is a managed Kubernetes service. That means that Amazon Web Services (AWS) handles some of the deployment and management tasks for users. But the fact that EKS is a managed service doesn’t mean that AWS manages all administrative tasks.

Application performance management (APM) and distributed tracing are practices that many teams have been using for years to help detect and mitigate performance issues within applications—while the first one was born in the era of big single-host monoliths, the latter is especially useful for distributed applications that use a microservices architecture, in which tracing is critical for pinpointing the source of performance issues.

When you’re planning an application performance monitoring (APM) strategy, collecting metrics from storage services like Amazon S3 may not seem like a priority. After all, part of the point of object storage is that applications can read and write from storage buckets seamlessly, with minimal configuration and overhead.